Instructions to use CompiwerAI/Mtrini-SVL-1.1-Merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use CompiwerAI/Mtrini-SVL-1.1-Merged with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="CompiwerAI/Mtrini-SVL-1.1-Merged")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("CompiwerAI/Mtrini-SVL-1.1-Merged")
model = AutoModelForMultimodalLM.from_pretrained("CompiwerAI/Mtrini-SVL-1.1-Merged", device_map="auto")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use CompiwerAI/Mtrini-SVL-1.1-Merged with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "CompiwerAI/Mtrini-SVL-1.1-Merged"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CompiwerAI/Mtrini-SVL-1.1-Merged",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/CompiwerAI/Mtrini-SVL-1.1-Merged

SGLang

How to use CompiwerAI/Mtrini-SVL-1.1-Merged with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "CompiwerAI/Mtrini-SVL-1.1-Merged" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CompiwerAI/Mtrini-SVL-1.1-Merged",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "CompiwerAI/Mtrini-SVL-1.1-Merged" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CompiwerAI/Mtrini-SVL-1.1-Merged",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use CompiwerAI/Mtrini-SVL-1.1-Merged with Docker Model Runner:
```
docker model run hf.co/CompiwerAI/Mtrini-SVL-1.1-Merged
```

Mtrini-SVL-1.1-Merged / README.md

CompiwerAI

Create README.md

b4fe4dd verified about 1 month ago

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---
language:
  - en
  - ar
  - fr
  - ary
license: apache-2.0
library_name: transformers
base_model: Qwen/Qwen3-VL-8B-Instruct
pipeline_tag: text-generation
tags:
  - mtrini
  - compiwer-ai
  - qwen3-vl
  - reasoning
  - coding
  - mathematics
  - darija
  - moroccan-arabic
  - self-verifying-loop
---
# 🐪 Mtrini-SVL-1.1

## The model is out of the lab.

Mtrini-SVL-1.1 is an open-weight ~8B model developed by **Compiwer AI**, based on **Qwen3-VL-8B-Instruct**.

It was trained with a focus on:

- 🧠 Reasoning
- 💻 Coding
- 🧮 Mathematics
- 🇲🇦 Moroccan Darija
- 🌍 Multilingual tasks

And yes...

**It's a Mtrini. 🐪**

## 🔄 Self-Verifying Loop

**SVL = Self-Verifying Loop**

Our development concept:

```text
THINK
  ↓
CHECK
  ↓
IMPROVE
  ↓
REPEAT 🔄
The goal is to encourage the model to verify and refine its responses.
SVL is an ongoing research direction at Compiwer AI.
📚 Training
The final dataset contained 58,574 unique examples.
Dataset	Examples
🇲🇦 Moroccan Darija QA + Reasoning	2,170
💻 OpenCodeReasoning-2	30,000
🧮 OpenMathInstruct-2	30,000
⚡ Model Specs
Property	Value
Model	Mtrini-SVL-1.1
Base	Qwen3-VL-8B-Instruct
Parameters	~8B
Architecture	Qwen3-VL
Training	LoRA / PEFT
Precision	BF16
Training Context	4096 tokens
Dataset	58,574 unique examples
Developer	Compiwer AI
Origin	🇲🇦 Salé, Morocco
📊 Training Run
Steps: 3,661
Epochs: 1
Training Loss: 0.5855
Mean Token Accuracy: 83.55%
These metrics describe the training run and should not be treated as standardized benchmark scores.
🚀 Usage
from transformers import Qwen3VLForConditionalGeneration, AutoTokenizer
model_id = "CompiwerAI/Mtrini-SVL-1.1-Merged"
tokenizer = AutoTokenizer.from_pretrained(
    model_id,
    trust_remote_code=True
)
model = Qwen3VLForConditionalGeneration.from_pretrained(
    model_id,
    torch_dtype="auto",
    device_map="auto",
    trust_remote_code=True
)
⚠️ Limitations
Mtrini is an experimental open model.
It can hallucinate, generate incorrect code, misunderstand prompts, or produce incorrect mathematical answers.
Verify important outputs.
🌍 Why Mtrini?
AI shouldn't only be built by the biggest companies on Earth.
Mtrini is Compiwer AI's experiment in building open AI with a focus on:
🇲🇦 Moroccan language
🧠 Reasoning
💻 Coding
🧮 Mathematics
🤝 Open AI
Building AI For Everyone.
Built in Salé, Morocco 🇲🇦

	---
	language:
	- en
	- ar
	- fr
	- ary
	license: apache-2.0
	library_name: transformers
	base_model: Qwen/Qwen3-VL-8B-Instruct
	pipeline_tag: text-generation
	tags:
	- mtrini
	- compiwer-ai
	- qwen3-vl
	- reasoning
	- coding
	- mathematics
	- darija
	- moroccan-arabic
	- self-verifying-loop
	---

	# 🐪 Mtrini-SVL-1.1

	## The model is out of the lab.

	Mtrini-SVL-1.1 is an open-weight ~8B model developed by Compiwer AI, based on Qwen3-VL-8B-Instruct.

	It was trained with a focus on:

	- 🧠 Reasoning
	- 💻 Coding
	- 🧮 Mathematics
	- 🇲🇦 Moroccan Darija
	- 🌍 Multilingual tasks

	And yes...

	It's a Mtrini. 🐪

	## 🔄 Self-Verifying Loop

	SVL = Self-Verifying Loop

	Our development concept:

	```text
	THINK
	↓
	CHECK
	↓
	IMPROVE
	↓
	REPEAT 🔄

	The goal is to encourage the model to verify and refine its responses.

	SVL is an ongoing research direction at Compiwer AI.

	📚 Training

	The final dataset contained 58,574 unique examples.

	Dataset Examples
	🇲🇦 Moroccan Darija QA + Reasoning 2,170
	💻 OpenCodeReasoning-2 30,000
	🧮 OpenMathInstruct-2 30,000
	⚡ Model Specs
	Property Value
	Model Mtrini-SVL-1.1
	Base Qwen3-VL-8B-Instruct
	Parameters ~8B
	Architecture Qwen3-VL
	Training LoRA / PEFT
	Precision BF16
	Training Context 4096 tokens
	Dataset 58,574 unique examples
	Developer Compiwer AI
	Origin 🇲🇦 Salé, Morocco
	📊 Training Run
	Steps: 3,661
	Epochs: 1
	Training Loss: 0.5855
	Mean Token Accuracy: 83.55%

	These metrics describe the training run and should not be treated as standardized benchmark scores.

	🚀 Usage
	from transformers import Qwen3VLForConditionalGeneration, AutoTokenizer

	model_id = "CompiwerAI/Mtrini-SVL-1.1-Merged"

	tokenizer = AutoTokenizer.from_pretrained(
	model_id,
	trust_remote_code=True
	)

	model = Qwen3VLForConditionalGeneration.from_pretrained(
	model_id,
	torch_dtype="auto",
	device_map="auto",
	trust_remote_code=True
	)
	⚠️ Limitations

	Mtrini is an experimental open model.

	It can hallucinate, generate incorrect code, misunderstand prompts, or produce incorrect mathematical answers.

	Verify important outputs.

	🌍 Why Mtrini?

	AI shouldn't only be built by the biggest companies on Earth.

	Mtrini is Compiwer AI's experiment in building open AI with a focus on:

	🇲🇦 Moroccan language
	🧠 Reasoning
	💻 Coding
	🧮 Mathematics
	🤝 Open AI

	Building AI For Everyone.

	Built in Salé, Morocco 🇲🇦